diff --git a/pynapple/process/signal_processing.py b/pynapple/process/signal_processing.py
index 5f4e969e..245825f7 100644
--- a/pynapple/process/signal_processing.py
+++ b/pynapple/process/signal_processing.py
@@ -53,7 +53,7 @@ def compute_welch_spectrum(sig, fs=None):
     return spectogram, freqs
 
 
-def morlet(M=1024, ncycles=1.5, scaling=1.0, precision=8):
+def _morlet(M=1024, ncycles=1.5, scaling=1.0, precision=8):
     """
     Defines the complex Morelet wavelet kernel
 
@@ -235,7 +235,7 @@ def _convolve_wavelet(
     """
     if norm not in ["sss", "amp"]:
         raise ValueError("Given `norm` must be `sss` or `amp`")
-    morlet_f = morlet(int(2**precision), ncycles=n_cycles, scaling=scaling)
+    morlet_f = _morlet(int(2**precision), ncycles=n_cycles, scaling=scaling)
     x = np.linspace(-8, 8, int(2**precision))
     int_psi = np.conj(_integrate(morlet_f, x[1] - x[0]))
     scale = scaling / (freq / fs)
diff --git a/tests/test_signal_processing.py b/tests/test_signal_processing.py
new file mode 100644
index 00000000..8da68921
--- /dev/null
+++ b/tests/test_signal_processing.py
@@ -0,0 +1,37 @@
+"""Tests of `signal_processing` for pynapple"""
+
+import numpy as np
+import pytest
+
+import pynapple as nap
+
+
+def test_compute_spectrum():
+    t = np.linspace(0, 1, 1024)
+    sig = nap.Tsd(d=np.random.random(1024), t=t)
+    r = nap.compute_spectrum(sig)
+    assert len(r[1]) == 1024
+    assert len(r[0]) == 1024
+    assert r[0].dtype == np.complex128
+    assert r[1].dtype == np.float64
+
+
+def test_compute_welch_spectrum():
+    t = np.linspace(0, 1, 1024)
+    sig = nap.Tsd(d=np.random.random(1024), t=t)
+    r = nap.compute_welch_spectrum(sig)
+    assert r[0].dtype == np.float64
+    assert r[1].dtype == np.float64
+
+
+def test_compute_wavelet_transform():
+    t = np.linspace(0, 1, 1024)
+    sig = nap.Tsd(d=np.random.random(1024), t=t)
+    freqs = np.linspace(1, 600, 10)
+    mwt = nap.compute_wavelet_transform(sig, fs=None, freqs=freqs)
+    assert mwt.shape == (1024, 10)
+
+    sig = nap.TsdFrame(d=np.random.random((1024, 4)), t=t)
+    freqs = np.linspace(1, 600, 10)
+    mwt = nap.compute_wavelet_transform(sig, fs=None, freqs=freqs)
+    assert mwt.shape == (1024, 10, 4)